Paper Citation Record · LEDGER

Ask Me Anything: A simple strategy for prompting language models

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2210.02441.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2210.02441 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:34:34.401058Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-23T06:57:40.125720Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 864c92e4-f26c-4ced-9cfd-c20d113d2245 · inbound

Emergent Abilities of Large Language Models cites this paper.

Emergent Abilities of Large Language Models Ask Me Anything: A simple strategy for prompting language models

Reference 5

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T07:38:38.006224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 7934065c-4cf0-41db-8e9a-75fa2ab4e361 · inbound

ART: Automatic multi-step reasoning and tool-use for large language models cites this paper.

ART: Automatic multi-step reasoning and tool-use for large language models Ask Me Anything: A simple strategy for prompting language models

Reference 137

Resolution: metadata mismatch; arxiv_id, observed 2026-05-16T19:03:06.197700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation bb91a987-19ce-4e3d-8c75-3bb16ff32ce0 · inbound

Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes cites this paper.

Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes Ask Me Anything: A simple strategy for prompting language models

Reference 63

Resolution: verified exact; arxiv_id, observed 2026-05-21T20:50:09.378763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 65617d68-2cb2-49f0-9ef3-0a4197a80279 · inbound

FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance cites this paper.

FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance Ask Me Anything: A simple strategy for prompting language models

Reference 1

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T19:56:45.450814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 075e787e-d5bd-4e8c-b9f3-35e0e17f0f78 · inbound

FDM-Bench: A Comprehensive Benchmark for Evaluating Large Language Models in Additive Manufacturing Tasks cites this paper.

FDM-Bench: A Comprehensive Benchmark for Evaluating Large Language Models in Additive Manufacturing Tasks Ask Me Anything: A simple strategy for prompting language models

Reference 43

Resolution: verified exact; arxiv_id, observed 2026-05-23T06:57:40.128690Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 8f1f1dc1-ba6e-4397-8965-1e37547302d9 · inbound

Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems cites this paper.

Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems Ask Me Anything: A simple strategy for prompting language models

Reference 116

Resolution: metadata mismatch; arxiv_id, observed 2026-05-22T21:42:10.870414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 7ad3d959-c4a9-4b84-a672-e3baedad3c0d · inbound

Enhancing the Safety of Medical Vision-Language Models by Synthetic Demonstrations cites this paper.

Enhancing the Safety of Medical Vision-Language Models by Synthetic Demonstrations Ask Me Anything: A simple strategy for prompting language models

Reference 3

Resolution: metadata mismatch; arxiv_id, observed 2026-05-19T10:57:16.494064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 42834d90-8dac-4fca-9426-09d3162565ad · inbound

In-Context Learning as an Effective Estimator of Functional Correctness of LLM-Generated Code cites this paper.

In-Context Learning as an Effective Estimator of Functional Correctness of LLM-Generated Code Ask Me Anything: A simple strategy for prompting language models

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T19:34:34.401058Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a7e47833-38d1-4aa7-9982-e4fe12197f44 · inbound

The Fourier Spectral Transformer Networks For Efficient and Generalizable Nonlinear PDEs Prediction cites this paper.

The Fourier Spectral Transformer Networks For Efficient and Generalizable Nonlinear PDEs Prediction Ask Me Anything: A simple strategy for prompting language models

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T19:27:46.651835Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b775d29f-7162-4589-b7eb-43e426c3fb62 · inbound

Power and Limitations of Aggregation in Compound AI Systems cites this paper.

Power and Limitations of Aggregation in Compound AI Systems Ask Me Anything: A simple strategy for prompting language models

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-02T21:09:48.568672Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 89803ffe-7c3e-4d9a-a082-7e9ea0825dd2 · inbound

C-TRAIL: A Commonsense World Framework for Trajectory Planning in Autonomous Driving cites this paper.

C-TRAIL: A Commonsense World Framework for Trajectory Planning in Autonomous Driving Ask Me Anything: A simple strategy for prompting language models

Reference 25

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T23:28:26.040988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4015d234-027c-441a-8fed-8f406d2a3a3c · inbound

How Language Models Process Out-of-Distribution Inputs: A Two-Pathway Framework cites this paper.

How Language Models Process Out-of-Distribution Inputs: A Two-Pathway Framework Ask Me Anything: A simple strategy for prompting language models

Reference 31

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T15:31:20.984585Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.